investment decisions. The used risk attribution quantification models GARCH (1.1), EGARCH (1.1), GARCH-M (1.1) and TGARCH (1 … concentration of investment funds (in Bulgaria) through the testing of complex, analytical and specialized models from the GARCH … models GARCH, EGARCH, GARCH-M and TGARCH with specification (1.1). The research covers the net balance sheet value of forty …

market uncertainty and volatility of the investment instruments. Thus, the prediction of the uncertainty and volatilities of … of ARCH effect has been tried to predict with conditional variance models such as ARCH (1), ARCH (2), ARCH (3), GARCH (1 …,1), GARCH (1,2), GARCH (1,3), GARCH (2,1), GARCH (2,2), EGARCH (1,1) and EGARCH (1,2). While the obtained findings indicate that …

This study investigates the volatility in daily stock returns for Total Nigeria Plc using nine variants of GARCH models … approach. We found from the results of the estimations that the persistence of the GARCH models are stable except for few cases …

the best fitting model among SGARCH, EGARCH and GJR-GARCH. In a bid to account for the dynamic and persistent nature of …

evaluate the model's suitability for prediction. The study\'s findings demonstrate the GARCH effect inside the ESG return … from 26 October 2017 and 31 March 2023 in the case of India. In this study, we utilized GARCH (Generalized Autoregressive … ESG index, the GARCH model is more appropriate than the LSTM model. …

-based Predictive Model (EFPM). Then, we combine it with the Copula-GARCH simulation model and the Mean-Conditional Value at Risk (Mean …